1. Field of the Invention
The invention relates in general to a multi-input multi-output (MIMO) system, and more particularly to a sphere decoding method applied to a MIMO system, which is capable of reducing system complexity.
2. Description of the Related Art
Along with development of wireless communication technology, a wireless local area network has been improved from a single-input single-output (SISO) mode 802.11a/b/g to a MIMO mode 802.11n to meet the requirement of higher-speed data transmission. The MIMO technology uses multiple transmission antennas and reception antennas for respectively transmitting and receiving signals. Compared to the conventional SISO system, the MIMO system can provide multiple parallel data streams at the same time and the same frequency band, thereby the data transmission amount being increased by multiples.
The MIMO system has to efficiently use an equivalent orthogonal characteristic channel in space to transmit the multiple parallel streams in the same frequency band. However, the equivalent orthogonal characteristic channel is usually degraded to a different extent depending on geometric configuration and device features of the transmission and reception antennas and geometric and statistic features of the transmission paths. Therefore, signal detection is an essential subject in design of the MIMO system. In general, complexity of a signal estimation system is raised for reducing the error rate of signal reception.
In the present signal estimation methods, the maximum likelihood (ML) rule can provide the optimal receiving performance, but raises the complexity of the signal estimation system to a too-high extent, causing difficulty in hardware implementation. Therefore, a sphere decoding method is developed to simultaneously have a receiving performance close to that of the maximum likelihood method and suitable system complexity. The sphere decoding method includes the depth first search rule and the breadth first search rule. Both search rules can reach the receiving performance of the maximum likelihood rule by suitable parameter settings, but requires huge estimation complexity. Therefore, how to effectively reduce the estimation complexity of the sphere decoding method has become an important issue to be solved in the present design of the MIMO system.